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Taufik Cahya Prayitna
Universitas Ahmad Dahlan
Computer Science & IT

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Classification of batik in southern coast area of java using convolutional neural network method Taufik Cahya Prayitna; Murinto Murinto
Jurnal Informatika Vol 15, No 3 (2021): September 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jifo.v15i2.a20692

Abstract

Batik is a craft inherited from our ancestors from the archipelago which has a high aesthetic value. Batik has several kinds of motives. Perhaps only a few of the information related to batik can find out. Therefore, not everyone can know or recognize batik in the southern coastal areas of Java correctly. Convolutional Neural Network is a part of deep learning that can be used to recognize and detect objects in digital images. Convolutional Neural Network is a type of Artificial Neural Network that was created specifically so that it can work on data in the form of an array. Based on the results of the study, the results obtained were 100% accuracy for the training process and 99% for the testing process with 630 training data and 180 validation data. The accuracy results obtained by testing the model are 93,3 % with 90 test data. So it can be concluded that the CNN model that has been created can classify batik motifs well.
Co-Authors Murinto Murinto